Poisson Model of Spike Generation

David Heeger(2000), Poisson Model of Spike Generation



In [2]:

    
using Revise, NeuroAnalysis, Interact
rate = slider(0:100,value=50,label="Spike Rate")
duration = slider(0:5000,value=1000,label="Spike Train Duration")
refreshperiod = slider(1:5,value=2,label="Spike Refresh Period")
ntrain = slider(1:1000,value=100,label="Number of Spike Train")
vbox(rate,duration,refreshperiod,ntrain)









    Out[2]:

Homogeneous Poisson Process, where instantaneous ﬁring rate is constant

Inter-Spike-Interval Exponential Distribution Method



In [3]:

    
sts = [poissonspike(rate[],duration[],rp=refreshperiod[]) for _ in 1:ntrain[]]
plotspiketrain(sts,timeline=[0,duration[]])









    Out[3]:

Instantaneous Firing Rate Method



In [4]:

    
sts = [poissonspike(t->rate[],duration[],rp=refreshperiod[]) for _ in 1:ntrain[]]
plotspiketrain(sts,timeline=[0,duration[]])









    Out[4]:

Inhomogeneous Poisson Process, where instantaneous ﬁring rate is changing



In [5]:

    
sts = [poissonspike(t->rate[]*(sin(0.05t)+1),duration[],rp=refreshperiod[]) for _ in 1:ntrain[]]
plotspiketrain(sts,timeline=[0,duration[]])









    Out[5]:



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